Diabetes is taking a growing toll on the social and economic wellbeing. For example, in the United States, 8.3% of the population, an equivalent of 25.8 million children and adults, are diagnosed with the condition. In 2012, diagnosed diabetes incurred a cost of $245 billion, up 41% from 2007. Hypoglycemia-related hospitalizations cost as much as $48,000 dollars per event, which adds up to billions of dollars annually.
Traditionally, for people with diabetes, regular blood glucose level testing has been used to obtain blood glucose readings and to monitor lifestyle effects on blood glucose level. For example, some healthcare professionals may instruct a patient to obtain blood glucose readings six to twelve times a day so that the patient may observe the changes associated with particular events or time of the day. In order to obtain blood glucose readings, the patient can input blood samples into a glucose meter. The glucose meter then analyzes the blood samples and generates blood glucose readings.
Some glucose meters have limited tagging ability to associate one or more readings with attributes, such as date and time or whether the reading was immediately after a meal. However, such limited tagging ability cannot provide a clear picture of life style patterns related to a patient's blood glucose readings before, during, and after hypoglycemic events. Some conventional diabetes management systems provide limited hypoglycemic data analysis, and do not relate a patient's blood glucose readings with hypoglycemic events. Doctors and patients are often not recording symptoms, causes, and treatments properly, and thus fail to recognize lifestyle patterns that cause hypoglycemic events.